Unexpected Test Losses from Generalization Theory
Dive into generalization theory's impact on unexpected test losses, exploring emerging settings and their implications for machine learning models.
GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models
Explore the limitations of mathematical reasoning in large language models through a synthetic dataset. Gain insights into LLM performance on high-school level math questions and understand the challenges in assessing their true capabilities.
General Linear Models - Regression
Comprehensive exploration of linear regression models, covering simple and multiple regression techniques, statistical inference, model diagnostics, and advanced topics for in-depth statistical analysis.
Machine Learning Tutorials for Data Science
Comprehensive tutorials covering machine learning fundamentals for data science, ideal for beginners seeking to understand key concepts and applications in the field.
Convolution in One Dimension for Neural Networks
Comprehensive exploration of 1D convolution in neural networks, covering theory, implementation, and practical application for time series data analysis and model building.
Learn TensorFlow and Deep Learning Fundamentals with Python - Code-First Introduction Part 2/2
Dive deep into TensorFlow and Python, mastering non-linear models, multi-class classification, and advanced techniques for optimizing neural networks and evaluating their performance.
Machine Learning Crash Course With ML.NET
Comprehensive introduction to machine learning concepts and hands-on demonstration using ML.NET, covering key processes from data loading to model evaluation with practical C# examples.
What Do Our Models Learn? - Aleksander Mądry
Exploring machine learning model behavior, biases in datasets, and challenges in dataset creation and replication for more robust and reliable AI systems.
Evaluating Classifiers in Python - Precision, Recall and F1 Score
Learn to evaluate machine learning classifiers using precision, recall, and F1 score in Python. Practical tutorial with code examples for accurate model assessment in Hindi.
Precision, Recall, Confusion Matrix and F1-Score - Machine Learning Tutorials in Hindi
Aprenda a evaluar modelos de aprendizaje automático utilizando métricas clave como precisión, recall, matriz de confusión y puntuación F1, con ejemplos prácticos en Python.
Microsoft Phi3 Mini 4K Instruct - Chain of Thought Prompting Test en Español
Explora pruebas de prompts de Cadena de Pensamiento con Microsoft Phi3 Mini 4K, comparando con otros modelos y técnicas de ajuste fino para razonamiento mejorado.
MLOps: Optimización PEFT para Resumen de Diálogos con Flan-T5 (LoRA) - Español
Aprende a optimizar modelos Flan-T5 con PEFT (Lora) para resumir diálogos eficientemente, incluyendo técnicas de prompt tuning y evaluación de resultados.
LLMOps: Prompt Tuning for Dialog Summarization with Flan-T5 in Spanish
Aprende a personalizar y evaluar modelos Flan-T5 para resumen de documentos mediante prompt tuning, con enfoque práctico en español.
Google PALM2 - Is It Better Than GPT4?
Explore the capabilities of Google's PALM2 language model and compare its performance to GPT-4, examining key features and potential applications in AI technology.
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models
Explore privacy risks of interactive LLMs, examining evaluation frameworks and proposing research directions for improved privacy auditing and mitigation strategies.
How a Data Scientist Fights Fraud - With Code!
Explore data science techniques for fraud detection, including feature engineering, SQL querying, model creation, evaluation, and interpretation, with hands-on coding examples.
How to Solve Santander Kaggle Transaction Competition - Top 1% Solution, No Ensemble
Learn to achieve top 1% in Santander Kaggle competition using neural networks, feature engineering, and data analysis techniques. Improve your machine learning skills with practical insights and strategies.
Data Science Solutions with Cortana Analytics
Comprehensive tutorial on building predictive models using Microsoft Azure Machine Learning, covering data processing, model creation, deployment, and practical applications in various domains.
Kaggle Competition Starter Notebook Walkthrough
Learn to create a starter notebook for a Kaggle competition, covering feature engineering, cross-validation, and LightGBM modeling. Gain practical insights from a Kaggle Grandmaster on predictive modeling and Python coding.
Machine Learning with DataRobot AI Cloud Platform
Comprehensive tutorial on DataRobot AI Cloud Platform, covering machine learning model building, evaluation, and deployment. Explores key features like AutoML, bias detection, and model optimization.
Solving Business Problems with Data - Delivering Value Through Use Case Deconstruction
Explore strategies for aligning data teams with business goals, focusing on use case deconstruction and value delivery. Learn to bridge the gap between technical expertise and practical business impact.